Estimated Interval-Based Checkpointing (EIC) on Spot Instances in Cloud Computing
In cloud computing, users can rent computing resources from service providers according to their demand. Spot instances are unreliable resources provided by cloud computing services at low monetary cost. When users perform tasks on spot instances, there is an inevitable risk of failures that causes...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/217547 |
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| author | Daeyong Jung JongBeom Lim Heonchang Yu Taeweon Suh |
| author_facet | Daeyong Jung JongBeom Lim Heonchang Yu Taeweon Suh |
| author_sort | Daeyong Jung |
| collection | DOAJ |
| description | In cloud computing, users can rent computing resources from service providers according to their demand. Spot instances are unreliable resources provided by cloud computing services at low monetary cost. When users perform tasks on spot instances, there is an inevitable risk of failures that causes the delay of task execution time, resulting in a serious deterioration of quality of service (QoS). To deal with the problem on spot instances, we propose an estimated interval-based checkpointing (EIC) using weighted moving average. Our scheme sets the thresholds of price and execution time based on history. Whenever the actual price and the execution time cross over the thresholds, the system saves the state of spot instances. The Bollinger Bands is adopted to inform the ranges of estimated cost and execution time for user's discretion. The simulation results reveal that, compared to the HBC and REC, the EIC reduces the number of checkpoints and the rollback time. Consequently, the task execution time is decreased with EIC by HBC and REC. The EIC also provides the benefit of the cost reduction by HBC and REC, on average. We also found that the actual cost and execution time fall within the estimated ranges suggested by the Bollinger Bands. |
| format | Article |
| id | doaj-art-a7c12ea6775b4151a4702807519b2989 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-a7c12ea6775b4151a4702807519b29892025-02-03T01:32:43ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/217547217547Estimated Interval-Based Checkpointing (EIC) on Spot Instances in Cloud ComputingDaeyong Jung0JongBeom Lim1Heonchang Yu2Taeweon Suh3Department of Computer Science Education, Korea University, Seoul, Republic of KoreaDepartment of Computer Science Education, Korea University, Seoul, Republic of KoreaDepartment of Computer Science Education, Korea University, Seoul, Republic of KoreaDepartment of Computer Science Education, Korea University, Seoul, Republic of KoreaIn cloud computing, users can rent computing resources from service providers according to their demand. Spot instances are unreliable resources provided by cloud computing services at low monetary cost. When users perform tasks on spot instances, there is an inevitable risk of failures that causes the delay of task execution time, resulting in a serious deterioration of quality of service (QoS). To deal with the problem on spot instances, we propose an estimated interval-based checkpointing (EIC) using weighted moving average. Our scheme sets the thresholds of price and execution time based on history. Whenever the actual price and the execution time cross over the thresholds, the system saves the state of spot instances. The Bollinger Bands is adopted to inform the ranges of estimated cost and execution time for user's discretion. The simulation results reveal that, compared to the HBC and REC, the EIC reduces the number of checkpoints and the rollback time. Consequently, the task execution time is decreased with EIC by HBC and REC. The EIC also provides the benefit of the cost reduction by HBC and REC, on average. We also found that the actual cost and execution time fall within the estimated ranges suggested by the Bollinger Bands.http://dx.doi.org/10.1155/2014/217547 |
| spellingShingle | Daeyong Jung JongBeom Lim Heonchang Yu Taeweon Suh Estimated Interval-Based Checkpointing (EIC) on Spot Instances in Cloud Computing Journal of Applied Mathematics |
| title | Estimated Interval-Based Checkpointing (EIC) on Spot Instances in Cloud Computing |
| title_full | Estimated Interval-Based Checkpointing (EIC) on Spot Instances in Cloud Computing |
| title_fullStr | Estimated Interval-Based Checkpointing (EIC) on Spot Instances in Cloud Computing |
| title_full_unstemmed | Estimated Interval-Based Checkpointing (EIC) on Spot Instances in Cloud Computing |
| title_short | Estimated Interval-Based Checkpointing (EIC) on Spot Instances in Cloud Computing |
| title_sort | estimated interval based checkpointing eic on spot instances in cloud computing |
| url | http://dx.doi.org/10.1155/2014/217547 |
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